Study On Optimization Of Gene Sequence Alignment Algorithm

In 1990, the human genome project(HGP) officially started, the program is known as the lifesciences "Appollo lunar program",With the implementation of the plan, the biological data related to theexplosive growth of.How to process the massive biological data, has become the urgent problem to besolved.Bioinformatics integration of molecule biology, computer science, mathematics, and provides anew method for the treatment of biological data of the increasing.In the study of bioinformatics, themost basic question is biological sequence analysis,Sequence alignment is a basic operation, it is veryimportant for the discovery of functional significance, structure and evolutionary information inbiological sequences.How to develop efficient sequence alignment algorithm is accurately a difficultproblem in sequence alignment at present,this paper is based on the above background to research onsequence alignment problem.Firstly, the present situation of the research on sequence alignment problem is briefly analyzed, andsummarize the basic knowledge of bioinformatics.Then in-depth studies of the sequence alignmentproblem, the classical pairwise sequence alignment algorithm: Needleman-Wunsch algorithm,Smith-Waterman algorithm and the lattice diagram method were systematically discussed.Then wediscussed the precise alignment algorithm, progressive alignment algorithm, iterative algorithm.Onseveral commonly used algorithm based on the idea of these three algorithms are outlined.Finally, this paper takes the multiple sequence alignment as the research object, introduces geneticalgorithm.According to the characteristic of genetic algorithm, the genetic algorithm coding method,genetic operators, selection operator and other aspects of the re design, the genetic algorithm has beenoptimized to a certain extent.Using the optimization of genetic algorithm for multiple sequencealignment.By the way of experiments, to set experimental environment, experimentalparameters,Compared with other algorithms.From the analysis of experimental results and theexperimental point of view to evaluate the improved algorithm.